ResearchSpace

BFROST: binary features from robust orientation segment tests accelerated on the GPU

Show simple item record

dc.contributor.author Cronje, J
dc.date.accessioned 2011-12-12T12:50:44Z
dc.date.available 2011-12-12T12:50:44Z
dc.date.issued 2011-11
dc.identifier.citation Cronje, J. 2011. BFROST: binary features from robust orientation segment tests accelerated on the GPU. 22nd Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Emerald Casino and Resort, Vanderbijlpark, South Africa, 22-25 November 2011 en_US
dc.identifier.uri http://hdl.handle.net/10204/5387
dc.description 22nd Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Emerald Casino and Resort, Vanderbijlpark, South Africa, 22-25 November 2011 en_US
dc.description.abstract A fast local image feature detector and descriptor that is implementable on the GPU is proposed. This method is the first GPU implementation of the popular FAST detector. A simple but novel method of feature orientation estimation which can be calculated in constant time is proposed. The robustness and reliability of our orientation estimation is validated against rotation invariant descriptors such as SIFT and SURF. Furthermore, a binary feature descriptor is proposed which is robust to noise, scalable, rotation invariant, fast to compute in parallel and maintains low memory consumption. The proposed method demonstrates good robustness and very fast computation times, making it usable in real-time applications. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Workflow request;7659
dc.subject Computer vision en_US
dc.subject Feature detection en_US
dc.subject Feature extraction en_US
dc.subject FAST detector en_US
dc.subject BFROST en_US
dc.subject Pattern recognition association en_US
dc.subject PRASA 2011 en_US
dc.title BFROST: binary features from robust orientation segment tests accelerated on the GPU en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Cronje, J. (2011). BFROST: binary features from robust orientation segment tests accelerated on the GPU. http://hdl.handle.net/10204/5387 en_ZA
dc.identifier.chicagocitation Cronje, J. "BFROST: binary features from robust orientation segment tests accelerated on the GPU." (2011): http://hdl.handle.net/10204/5387 en_ZA
dc.identifier.vancouvercitation Cronje J, BFROST: binary features from robust orientation segment tests accelerated on the GPU; 2011. http://hdl.handle.net/10204/5387 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Cronje, J AB - A fast local image feature detector and descriptor that is implementable on the GPU is proposed. This method is the first GPU implementation of the popular FAST detector. A simple but novel method of feature orientation estimation which can be calculated in constant time is proposed. The robustness and reliability of our orientation estimation is validated against rotation invariant descriptors such as SIFT and SURF. Furthermore, a binary feature descriptor is proposed which is robust to noise, scalable, rotation invariant, fast to compute in parallel and maintains low memory consumption. The proposed method demonstrates good robustness and very fast computation times, making it usable in real-time applications. DA - 2011-11 DB - ResearchSpace DP - CSIR KW - Computer vision KW - Feature detection KW - Feature extraction KW - FAST detector KW - BFROST KW - Pattern recognition association KW - PRASA 2011 LK - https://researchspace.csir.co.za PY - 2011 T1 - BFROST: binary features from robust orientation segment tests accelerated on the GPU TI - BFROST: binary features from robust orientation segment tests accelerated on the GPU UR - http://hdl.handle.net/10204/5387 ER - en_ZA


Files in this item

Thumbnail
Name: Cronje_2011.pdf
Size: 905.6Kb
Format: PDF
View/Open

This item appears in the following Collection(s)

Show simple item record